relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2369/
title: An Improved Artificial Immune Network For Solving Construction Site Layout Optimization
creator: Vu, Duc Quang
creator: Nguyen, Van Truong
creator: Hoang, Xuan-Huan
subject: Information Technology (IT)
description: Nature-inspired algorithms are often used to find optimal solutions for many combinatorial problems. An immune inspired algorithm, opt-aiNet algorithm, is well known for func- tion optimization. In this paper, we develop a combination of local search with opt-aiNet, called lopt-aiNet, to solve construction site layout (CSL) problem. The effectiveness of the proposed algorithm is investigated through experiments on some datasets taken from the state-of-art and a randomly created dataset. Ex- perimental results show that the lopt-aiNet can produce optimal transportation cost with lower run time compared to the site layouts generated by metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and aiNet.
date: 2016
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2369/1/QuangRIVF.pdf
identifier:   Vu, Duc Quang and Nguyen, Van Truong and Hoang, Xuan-Huan  (2016) An Improved Artificial Immune Network For Solving Construction Site Layout Optimization.  In: RIVF 2016.